ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference

Tools for assessing and diagnosing convergence of Markov Chain Monte Carlo simulations, as well as for graphically display results from full MCMC analysis. The package also facilitates the graphical interpretation of models by providing flexible functions to plot the results against observed variables.

Install the latest version of this package by entering the following in R:
install.packages("ggmcmc")
AuthorXavier Fernández i Marín <xavier.fim@gmail.com>
Date of publication2016-06-28 23:48:06
MaintainerXavier Fernández i Marín <xavier.fim@gmail.com>
LicenseGPL-2
Version1.1
http://xavier-fim.net/packages/ggmcmc, https://github.com/xfim/ggmcmc

View on CRAN

Man pages

ac: Calculate the autocorrelation of a single chain, for a...

calc_bin: Calculate binwidths by parameter, based on the total number...

ci: Calculate Credible Intervals (wide and narrow).

custom.sort: Auxiliary function that sorts Parameter names taking into...

get_family: Subset a ggs object to get only the parameters with a given...

ggmcmc: Wrapper function that creates a single pdf file with all...

ggs: Import MCMC samples into a ggs object than can be used by all...

ggs_autocorrelation: Plot an autocorrelation matrix

ggs_caterpillar: Caterpillar plot with thick and thin CI

ggs_chain: Auxiliary function that extracts information from a single...

ggs_compare_partial: Density plots comparing the distribution of the whole chain...

ggs_crosscorrelation: Plot the Cross-correlation between-chains

ggs_density: Density plots of the chains

ggs_geweke: Dotplot of the Geweke diagnostic, the standard Z-score

ggs_histogram: Histograms of the paramters.

ggs_pairs: Create a plot matrix of posterior simulations

ggs_ppmean: Posterior predictive plot comparing the outcome mean vs the...

ggs_ppsd: Posterior predictive plot comparing the outcome standard...

ggs_Rhat: Dotplot of Potential Scale Reduction Factor (Rhat)

ggs_rocplot: Receiver-Operator Characteristic (ROC) plot for models with...

ggs_running: Running means of the chains

ggs_separation: Separation plot for models with binary response variables

ggs_traceplot: Traceplot of the chains

gl_unq: Generate a factor with unequal number of repetitions.

radon: Simulations of the parameters of a hierarchical model using...

roc_calc: Calculate the ROC curve for a set of observed outcomes and...

s: Simulations of the parameters of a simple linear regression...

s.binary: Simulations of the parameters of a simple linear regression...

sde0f: Spectral Density Estimate at Zero Frequency.

s.y.rep: Simulations of the posterior predictive distribution of a...

y: Values for the observed outcome of a simple linear regression...

y.binary: Values for the observed outcome of a binary logistic...

Functions

ac Man page
calc_bin Man page
ci Man page
custom.sort Man page
get_family Man page
ggmcmc Man page
ggmcmc-package Man page
ggs Man page
ggs_autocorrelation Man page
ggs_caterpillar Man page
ggs_chain Man page
ggs_compare_partial Man page
ggs_crosscorrelation Man page
ggs_density Man page
ggs_geweke Man page
ggs_histogram Man page
ggs_pairs Man page
ggs_ppmean Man page
ggs_ppsd Man page
ggs_Rhat Man page
ggs_rocplot Man page
ggs_running Man page
ggs_separation Man page
ggs_traceplot Man page
gl_unq Man page
radon Man page
roc_calc Man page
s Man page
s.binary Man page
sde0f Man page
s.y.rep Man page
y Man page
y.binary Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.